Name
Abstract | ||
|---|---|---|
We develop a probabilistic framework for global modeling of the traffic over a computer network. The model integrates existing single-link (-flow) traffic models with the routing over the network to capture the global traffic behavior. It arises from a limit approximation of the traffic fluctuations as the time-scale and the number of users sharing the network grow. The resulting probability model is comprised of a Gaussian and/or a stable, infinite variance components. They can be succinctly described and handled by certain 'space-time' random fields. The model is validated against real data and applied to predict traffic fluctuations over unobserved links from a limited set of observed links. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/INFCOM.2010.5462246 | INFOCOM |
Keywords | Field | DocType |
global modeling,backbone network traffic,infinite variance component,gaussian process,computer networks,traffic fluctuation,space-time random field,gaussian processes,single-link traffic model,computer network,telecommunication traffic,telecommunication network routing,probabilistic framework,probability,limit set,predictive models,computational modeling,protocols,mathematical model,random field,fluctuations,statistics,routing,spine | Traffic generation model,Random field,Computer science,Flow (psychology),Computer network,Gaussian,Gaussian process,Backbone network,Network traffic simulation,Traffic equations,Distributed computing | Conference |
ISSN | ISBN | Citations |
0743-166X | 978-1-4244-5836-3 | 10 |
PageRank | References | Authors |
0.62 | 10 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stilian Stoev | 1 | 78 | 8.03 |
| George Michailidis | 2 | 303 | 35.19 |
| Joel Vaughan | 3 | 13 | 1.44 |